Insights into biodiversity and trophic webs are important for understanding ecosystem functions. Although the surfaces of glaciers are one of the most productive and biologically diverse parts of the cryosphere, the links between top consumers, their diet and microbial communities are poorly understood. In this study, for the first time we investigated the relationships between bacteria, fungi and other microeukaryotes as they relate to tardigrades, microscopic metazoans that are top consumers in cryoconite, a biologically rich and productive biogenic sediment found on glacier surfaces. Using metabarcoding (16S rDNA for bacteria, ITS1 for fungi, and 18S rDNA for other microeukaryotes), we analyzed the microbial community structures of cryoconite and compared them with the community found in both fully fed and starved tardigrades. The community structure of each microbial group (bacteria, fungi, microeukaryotes) were similar within each host group (cryoconite, fully fed tardigrades and starved tardigrades), and differed significantly between groups, as indicated by redundancy analyses. The relative number of operational taxonomic units (ZOTUs, OTUs) and the Shannon index differed significantly between cryoconite and tardigrades. Species indicator analysis highlighted a group of microbial taxa typical of both fully fed and starved tardigrades (potential commensals), like the bacteria of the genera Staphylococcus and Stenotrophomonas, as well as a group of taxa typical of both cryoconite and fully fed tardigrades (likely part of the tardigrade diet; bacteria Flavobacterium sp., fungi Preussia sp., algae Trebouxiophyceae sp.). Tardigrades are consumers of bacteria, fungi and other microeukaryotes in cryoconite and, being hosts for diverse microbes, their presence can enrich the microbiome of glaciers.

DNA metabarcoding offers new perspectives, especially with regard to the high‐throughput identification and diagnostics of pathogens. Microsporidia are an example of widely distributed, opportunistic and pathogenic microorganisms in which molecular identification is important for both environmental research and clinical diagnostics. We have developed a method for parallel detection of both microsporidian infection and the host species. We designed new primer sets: one specific for the classical Microsporidia (targeting the hypervariable V5 region of small subunit [ssu] rDNA), and a second one targeting a shortened fragment of the COI gene (standard metazoan DNA‐barcode); both markers are well suited for next generation sequencing. Analysis of the ssu rDNA data set representing 607 microsporidian species (120 genera) indicated that the V5 region enables identification of >98% species in the data set (596/607). To test the method, we used microsporidians that infect mosquitoes in natural populations. Using mini‐COI data, all field‐collected mosquitoes were unambiguously assigned to seven species; among them almost 60% of specimens were positive for at least 11 different microsporidian species, including a new microsporidian ssu rDNA sequence (Microsporidium sp. PL01). Phylogenetic analysis showed that this species belongs to one of the two main clades in the Terresporidia. We found a high rate of microsporidian co‐infections (9.4%). The numbers of sequence reads for the operational taxonomic units suggest that the occurrence of Nosema spp. in co‐infections could benefit them; however, this observation should be retested using a more intensive host sampling. Our results show that DNA barcoding is a rapid and cost‐effective method for deciphering sample diversity in greater resolution, including the hidden biodiversity that may be overlooked using classical methodology.

The animal gut microbiota consist of many different microorganisms, mainly bacteria, but archaea, fungi, protozoans, and viruses may also be present. This complex and dynamic community of microorganisms may change during parasitic infection. In the present study, we investigated the effect of the presence of microsporidians on the composition of the mosquito gut microbiota and linked some microbiome taxa and functionalities to infections caused by these parasites. We characterised bacterial communities of 188 mosquito females, of which 108 were positive for microsporidian DNA. To assess how bacterial communities change during microsporidian infection, microbiome structures were identified using 16S rRNA microbial profiling. In total, we identified 46 families and four higher taxa, of whichComamonadaceae,Enterobacteriaceae,FlavobacteriaceaeandPseudomonadaceaewere the most abundant mosquito-associated bacterial families. Our data suggest that the mosquito gut microbial composition varies among host species. In addition, we found a correlation between the microbiome composition and the presence of microsporidians. The prediction of metagenome functional content from the 16S rRNA gene sequencing suggests that microsporidian infection is characterised by some bacterial species capable of specific metabolic functions, especially the biosynthesis of ansamycins and vancomycin antibiotics and the pentose phosphate pathway. Moreover, we detected a positive correlation between the presence of microsporidian DNA and bacteria belonging toSpiroplasmataceaeandLeuconostocaceae, each represented by a single species,Spiroplasmasp. PL03 andWeissellacf.viridescens,respectively.Additionally,W.cf.viridescenswas observed only in microsporidian-infected mosquitoes. More extensive research, including intensive and varied host sampling, as well as determination of metabolic activities based on quantitative methods, should be carried out to confirm our results.